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A method for detection of somatic variants is presented for the intraoperative evaluation of tumor mutations in less than 30 min, using rapid DNA extraction, in silico optimized LAMP amplification, and a LAMP product analysis tool: LAMPrey.

Malignant primary brain tumors are the most common cancer in children aged 0–14 years, and are the most common cause of death among pediatric cancer patients. Compared to other cancers, pediatric brain tumors have been difficult to diagnose and study given the high risk of intracranial biopsy penetrating through vital midline structures, where the majority of pediatric brain tumors originate (Ostrom et al., 2015). Furthermore, the vast majority of these tumors recur. With limitations in the ability to monitor using clinical and radiographic methods alone, minimally invasive methods such as liquid biopsy will be crucial to our understanding and treatment. Liquid biopsy of blood, urine, and cerebrospinal fluid (CSF) can be used to sample cfDNA, ctDNA, RNA, extracellular vesicles, and tumor-associated proteins. In the past year, four seminal papers have made significant advances in the use of liquid biopsy in pediatric brain tumor patients (Liu et al., 2021; Cantor et al., 2022; Miller et al., 2022; Pagès et al., 2022). In this review, we integrate the results of these studies and others to discuss how the newest technologies in liquid biopsy are being developed for molecular diagnosis and treatment response in pediatric brain tumors.

Abstract We present SquiggleNet, the first deep-learning model that can classify nanopore reads directly from their electrical signals. SquiggleNet operates faster than DNA passes through the pore, allowing real-time classification and read ejection. Using 1 s of sequencing data, the classifier achieves significantly higher accuracy than base calling followed by sequence alignment. Our approach is also faster and requires an order of magnitude less memory than alignment-based approaches. SquiggleNet distinguished human from bacterial DNA with over 90% accuracy, generalized to unseen bacterial species in a human respiratory meta genome sample, and accurately classified sequences containing human long interspersed repeat elements.

Gliomas are tumors derived from mutations in glial brain cells. Gliomas cause significant morbidity and mortality and development of precision diagnostics and novel targeted immunotherapies are critically important. Radiographic imaging is the most common technique to diagnose and track response to treatment, but is an imperfect tool. Imaging does not provide molecular information, which is becoming critically important for identifying targeted immunotherapies and monitoring tumor evolution. Furthermore, immunotherapy induced inflammation can masquerade as tumor progression in images (pseudoprogression) and confound clinical decision making. More recently, circulating cell free tumor DNA (cf-tDNA) has been investigated as a promising biomarker for minimally invasive glioma diagnosis and disease monitoring. cf-tDNA is shed by gliomas into surrounding biofluids (e.g. cerebrospinal fluid and plasma) and, if precisely quantified, might provide a quantitative measure of tumor burden to help resolve pseudoprogression. cf-tDNA can also identify tumor genetic mutations to help guide targeted therapies. However, due to low concentrations of cf-tDNA, recovery and analysis remains challenging. Plasma cf-tDNA typically represents

We present a novel, compliant mechanism that provides the capability to navigate extremely confined spaces for the purpose of infrastructure inspection. Extremely confined spaces are commonly encountered during infrastructure inspection. Examples of such spaces can include pipes, conduits, and ventilation ducts. Often these infrastructure features go uninspected simply because there is no viable way to access their interior. In addition, it is not uncommon for extremely confined spaces to possess a maze-like architecture that must be selectively navigated in order to properly perform an inspection. Efforts by the imaging sensor community have resulted in the development of imaging sensors on the millimeter length scale. Due to their compact size, they are able to inspect many extremely confined spaces of interest, however, the means to deliver these sensors to the proper location to obtain the desired images are lacking. To address this problem, we draw inspiration from the field of endoscopic surgery. Specifically we consider the work that has already been done to create long flexible needles that are capable of being steered through the human body. These devices are typically referred to as ‘steerable needles.’ Steerable needle technology is not directly applicable to the problem of navigating maze-like arrangements of extremely confined spaces, but it does provide guidance on how this problem should be approached. Specifically, the super-elastic nitinol tubing material that allows steerable needles to operate is also appropriate for the problem of navigating maze-like arrangements of extremely confined spaces. Furthermore, the portion of the mechanism that enters the extremely confined space is completely mechanical in nature. The mechanical nature of the device is an advantage when the extremely confined space features environmental hazards such as radiation that could degrade an electromechanically operated mechanism. Here, we present a compliant mechanism developed to navigate maze-like arrangements of extremely confined spaces. The mechanism is shown to be able to selectively navigate past three 90° bends. The ability to selectively navigate extremely confined spaces opens up new possibilities to use emerging miniature imaging technology for infrastructure inspection. [ABSTRACT FROM AUTHOR]